System and method for evaluating media segments for interestingness

ABSTRACT

Disclosed herein are systems, methods, and computer-readable storage device for analyzing a first audiofile, to yield a first analysis, wherein the first analysis identifies a first segment of a first plurality of segments within the first audiofile, the first segment being one of a most interesting segment, a most important segment, a most relevant segment, and a most representative segment. A same analysis can be performed on a second audiofile, to yield a second analysis, wherein the second analysis identifies a second segment of a second plurality of segments within the second audiofile, the second segment comprising one of a most interesting segment, a most important segment, a most relevant segment, and a most representative segment. The first segment is presented as a representative segment of the first audiofile and the second segment is presented as a representative of the second audiofile within a three-dimensional audio space.

BACKGROUND

1. Technical Field

The present disclosure relates to analyzing audiofiles and identifyingrepresentative segments of the audiofiles for presentation to a user.

2. Introduction

Many organizations store important conversations and audio meetings in alarge repository of audio files. This allows users to play and listen toold or previous conversations at any time convenient to the user.However, as the number of audio files stored in a repository grows, itbecomes harder for users to locate specific conversations. Moreover,often times, the user is not interested in listening to an entireconversation, but simply wants to listen to a specific portion of theconversation that is of interest to the user. For example, the user maywish to only listen to a summary of the conversation, an introduction ofthe conversation participants, or a list of action items at the end ofthe conversation.

As the number of conversations in the repository grows, it becomes moredifficult to locate the specific portions desired because as the usermust first identify the file (i.e., the conversation) and then thespecific portion of interest from the file. If the user is not familiarwith the conversation, the user often must listen to a large portion ofthe conversation (if not the entire conversation) to determine if she isinterested in the conversation. Such solutions do not efficiently makethe user aware of what each conversation is about and can be improvedupon.

SUMMARY

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

Disclosed herein are approaches for analyzing audiofiles and identifyingrepresentative segments of the audiofiles for presentation to a user,particularly in a three-dimensional audio space.

A three-dimensional audio space is described in U.S. patent applicationSer. No. 13/728,467, the contents of which are incorporated herein inits entirety.

This disclosure deals with a system that allows users to obtain specificsegments or portions of a conversation as users browse through audiocontent in a three-dimensional audio space. More specifically, when theuser browses through audio in audio conversations, the system canpresent audio previews/snippets of each audio conversation, where theaudio previews/snippets can be the most interesting, recognizable,relevant, popular, and/or representative portions of the conversation.In other words, as the user browses through audio conversations, she canlisten to audio segments in each conversation to obtain a preview ofspecific conversations, providing search results for appropriatesegments by “highlighting” segments where specific markers identifykeywords/topics/information associated with the search are found inrecorded conversations. Such browsing can occur within a singular audioconversation or among multiple audio conversations.

An exemplary system, configured according to this disclosure, analyzes afirst audiofile, to yield a first analysis, wherein the first analysisidentifies a first segment of a first plurality of segments within thefirst audiofile, the first segment being one of a most interestingsegment, a most important segment, a most relevant segment, and a mostrepresentative segment. The system also performs the same analysis on asecond audiofile, to yield a second analysis, wherein the secondanalysis identifies a second segment of a second plurality of segmentswithin the second audiofile, the second segment comprising one of a mostinteresting segment, a most important segment, a most relevant segment,and a most representative segment. The system then presents the firstsegment as a representative segment of the first audiofile and thesecond segment as a representative of the second audiofile within athree-dimensional audio space.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIG. 1 illustrates an exemplary system embodiment;

FIG. 2 illustrates an exemplary network configuration;

FIG. 3 illustrates identification of various segments in a singleaudiofile;

FIG. 4 multiple audiofiles having identified segments; and

FIG. 5 illustrates an example method embodiment.

DETAILED DESCRIPTION

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

The present disclosure addresses analyzing audiofiles and identifyingrepresentative segments of the audiofiles for presentation to a user ina three-dimensional audio space. A system, method and computer-readablemedia are disclosed which perform such analyses and presentation. Abrief introductory description of a basic general purpose system orcomputing device in FIG. 1 which can be employed to practice theconcepts is disclosed herein. A more detailed description of analyzingaudiofiles for presentation of representative segments within athree-dimensional audiospace will then follow, accompanied by exemplaryvariations. These variations shall be described herein as the variousembodiments are set forth. The disclosure now turns to FIG. 1.

With reference to FIG. 1, an exemplary system 100 includes ageneral-purpose computing device 100, including a processing unit (CPUor processor) 120 and a system bus 110 that couples various systemcomponents including the system memory 130 such as read only memory(ROM) 140 and random access memory (RAM) 150 to the processor 120. Thesystem 100 can include a cache 122 of high speed memory connecteddirectly with, in close proximity to, or integrated as part of theprocessor 120. The system 100 copies data from the memory 130 and/or thestorage device 160 to the cache 122 for quick access by the processor120. In this way, the cache provides a performance boost that avoidsprocessor 120 delays while waiting for data. These and other modules cancontrol or be configured to control the processor 120 to perform variousactions. Other system memory 130 may be available for use as well. Thememory 130 can include multiple different types of memory with differentperformance characteristics. It can be appreciated that the disclosuremay operate on a computing device 100 with more than one processor 120or on a group or cluster of computing devices networked together toprovide greater processing capability. The processor 120 can include anygeneral purpose processor and a hardware module or software module, suchas module 1 162, module 2 164, and module 3 166 stored in storage device160, configured to control the processor 120 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. The processor 120 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

The system bus 110 may be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. A basicinput/output (BIOS) stored in ROM 140 or the like, may provide the basicroutine that helps to transfer information between elements within thecomputing device 100, such as during start-up. The computing device 100further includes storage devices 160 such as a hard disk drive, amagnetic disk drive, an optical disk drive, tape drive or the like. Thestorage device 160 can include software modules 162, 164, 166 forcontrolling the processor 120. Other hardware or software modules arecontemplated. The storage device 160 is connected to the system bus 110by a drive interface. The drives and the associated computer-readablestorage media provide nonvolatile storage of computer-readableinstructions, data structures, program modules and other data for thecomputing device 100. In one aspect, a hardware module that performs aparticular function includes the software component stored in a tangiblecomputer-readable storage medium in connection with the necessaryhardware components, such as the processor 120, bus 110, display 170,and so forth, to carry out the function. In another aspect, the systemcan use a processor and computer-readable storage medium to storeinstructions which, when executed by the processor, cause the processorto perform a method or other specific actions. The basic components andappropriate variations are contemplated depending on the type of device,such as whether the device 100 is a small, handheld computing device, adesktop computer, or a computer server.

Although the exemplary embodiment described herein employs the hard disk160, other types of computer-readable media which can store data thatare accessible by a computer, such as magnetic cassettes, flash memorycards, digital versatile disks, cartridges, random access memories(RAMs) 150, read only memory (ROM) 140, a cable or wireless signalcontaining a bit stream and the like, may also be used in the exemplaryoperating environment. Tangible computer-readable storage media,computer-readable storage devices, or computer-readable memory devices,expressly exclude media such as transitory waves, energy, carriersignals, electromagnetic waves, and signals per se.

To enable user interaction with the computing device 100, an inputdevice 190 represents any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 170 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems enable a user to provide multiple types of input to communicatewith the computing device 100. The communications interface 180generally governs and manages the user input and system output. There isno restriction on operating on any particular hardware arrangement andtherefore the basic features here may easily be substituted for improvedhardware or firmware arrangements as they are developed.

For clarity of explanation, the illustrative system embodiment ispresented as including individual functional blocks including functionalblocks labeled as a “processor” or processor 120. The functions theseblocks represent may be provided through the use of either shared ordedicated hardware, including, but not limited to, hardware capable ofexecuting software and hardware, such as a processor 120, that ispurpose-built to operate as an equivalent to software executing on ageneral purpose processor. For example the functions of one or moreprocessors presented in FIG. 1 may be provided by a single sharedprocessor or multiple processors. (Use of the term “processor” shouldnot be construed to refer exclusively to hardware capable of executingsoftware.) Illustrative embodiments may include microprocessor and/ordigital signal processor (DSP) hardware, read-only memory (ROM) 140 forstoring software performing the operations described below, and randomaccess memory (RAM) 150 for storing results. Very large scaleintegration (VLSI) hardware embodiments, as well as custom VLSIcircuitry in combination with a general purpose DSP circuit, may also beprovided.

The logical operations of the various embodiments are implemented as:(1) a sequence of computer implemented steps, operations, or proceduresrunning on a programmable circuit within a general use computer, (2) asequence of computer implemented steps, operations, or proceduresrunning on a specific-use programmable circuit; and/or (3)interconnected machine modules or program engines within theprogrammable circuits. The system 100 shown in FIG. 1 can practice allor part of the recited methods, can be a part of the recited systems,and/or can operate according to instructions in the recited tangiblecomputer-readable storage media. Such logical operations can beimplemented as modules configured to control the processor 120 toperform particular functions according to the programming of the module.For example, FIG. 1 illustrates three modules Mod1 162, Mod2 164 andMod3 166 which are modules configured to control the processor 120.These modules may be stored on the storage device 160 and loaded intoRAM 150 or memory 130 at runtime or may be stored in othercomputer-readable memory locations.

Having disclosed some components of a computing system, the disclosurenow turns to FIG. 2, which illustrates an exemplary networkconfiguration 200. In this configuration 200, a user 202 is interactingwith a computing device 204. The computing device 204 can be a desktopcomputer, a laptop, a tablet, a smartphone, a virtual computer, or anyother device having network connections and the capacity to presentcontent to the user. The user 202 uses the computing device 204 tobrowse through a repository 206 of audiofiles 208.

The browsing of the audiofiles 208 can occur in a variety of formats.For example, the user 202 can be presented with a list of the storedaudiofiles 208, where when the user moves a cursor on a computing devicedisplay to any particular audiofile a representative segment of thatparticular audiofile is played for the user. In other embodiments, theuser 202 can browse for a particular recording of a conference call inthe recorded audiofiles 208 using a three-dimensional audio space.

FIG. 3 illustrates identification of various segments in a singleaudiofile 300, which is performed as part of the analysis of anaudiofile 302. The system identifies segments 310, 312, 314corresponding to themes, categories, topics, or other areas of interestto a user, within the audiofile 302. For example, categories of segmentswhich the system can identify include a most interesting segment, a mostimportant segment, a most relevant segment, a most popular segment, anda most representative segment. In some cases, a single segment cancorrespond to more than one category, topic, or classification. Forexample, a single segment can be both the most popular and the mostinteresting segment of an audiofile.

Determining which segment is most interesting can rely on useridentities and preferences, context information, and/or trendinganalytics. For example, the user identity of the person browsing throughthe audiofiles may be associated with a job title which establisheswhich portions of the audiofiles is relevant. That is, the segment of anaudiofile which will be most interesting to a sports broadcaster mayvary from the segment which is most interesting to a fireman. If themost interesting segment is based on context information, the system canuse information such as time (time of day when the audiofile wasrecorded), location (of audiofile recording), a user identity of theuser, an age of each audiofile, a content of a browsing request, an ageof the user, and/or a category of the audiofile to determine whichsegment is the most interesting. Other algorithms for determining whichsegment of an audiofile is most interesting to a user can also be usedwithout deviating from the scope of this invention.

Some factors which can be used to determine popularity and/orinterestingness can be: a number of user-generated tags and/or comments(showing interest in a segment), a length of tags and/or comments for asegment (showing interest in a segment), a number of speakers (i.e.,turn taking) in a segment (showing interactiveness in a segment), adominance of certain speakers (e.g., the segments for which an authorityfigure may be featured more prominently), social media markers (such asratings, tags, ranking), and/or social cohesion of speakers with a userperforming the search (where social cohesion may be defined as arelationship strength between the speakers and the user based onhistory). Such factors are exemplary only, and other factors may be usedto determine how interesting a user will find a particular segment, orhow popular a segment is. Regarding popularity, such determinations canbe made based on geographic location, nationality, language, world-widepopularity, references on specific websites (rather than allweb-traffic), friends, business colleagues, or other groups ofindividuals.

Determining which segments are the most important, relevant, orrepresentative can use any of those same algorithms for determiningwhich segment is most interesting, tailoring those algorithms to selectsegments based on the particular feature being sought. For example, analgorithm may determine that a segment would be most interesting to auser based on listening patterns or history of a particular user,whereas which segment is most important can be determined based on whichsegment most closely aligns with the user's job title, and the segmentwhich is most relevant is based on a keyword search of words spoken bythe user in the past five minutes (or other time period).

The identification of the segments 310, 312, 314 can be further based onsearching an audiofile for specific keywords. The keywords can bespecific to a user or job title, or can be generic. For example, whensearching any audiofile which is a recording of a conference call, thevarious parties will generally introduce themselves. Therefore a list ofkeywords can search for words associated with introductions on aconference call, such as “This is xxx”, “I'm here,” etc. Other exemplaryword lists can include action items, goals, problems, achievements, andpersonnel. As the system performs a keyword search on an audiofile,specific instances 304, 306, 308 are identified as matching the keyword.

Searching the audiofile for the keywords can be a comparison of recordedaudio waveforms or by using a transcript to search for the keywords inconjunction with a timetable itemizing when the words were spoken. Asthe specific instances 304, 306, 308 of keywords are noted, the systemdefines a time period associated with each specific instance, where theidentified segment is the portion of the audiofile corresponding to thetime period defined. Often, the time period will (as illustrated) extendbefore and after the instance where the keyword was found. For example,as illustrated, words were identified in the audiofile 302 correspondingto identification of “Goals” at point 306, resulting in a segment 312being defined which extends before and after the point 306 where thegoal-related words were found. In other instances, the segment mightextend exclusively before or after the point where the trigger wordswere found.

FIG. 4 illustrates multiple audiofiles 402, 404, 406 having identifiedsegments 400. As the user browses the audiofiles 402, 404, 406, thesystem identifies one of the identified segments from each of theaudiofiles 402, 404, 406 as a representative segment for each audiofile.As the user browses each respective audiofile, the representativesegment identified by the system will be presented to the user.

Consider the second audiofile 404 where the system is seeking to presentsegments which are most important to a user. Only a single instance 418of words which are important to the user is found, corresponding to asingle segment 416. By contrast, the first audiofile 402 and the thirdaudiofile both have multiple instances of important words (412, 414,424, 426) resulting in each audiofile having multiple segments which areimportant (408, 410, 420, 422). In such circumstances, the systemperforms an additional analysis to determine which segment in themultiple segments for each audiofile is “more” important. Suchdetermination can be based on a frequency of words found on the keywordlist, a volume of the words being spoken, repetition of the words, orwho is speaking the words.

During presentation of the audiofiles 402, 404, 406, the system presentsthe representative segments to the user. In various embodiments, theuser can then select which of the audiofiles is sought. Such selectioncan be made by direct user input (such as a click, vocal selection,and/or motion indicating the selection) or by indirect user input(lingering on a particular audiofile, listening to portions other thanthe representative segment, etc.). In one embodiment, a user browsingthe audiofiles can be in a three-dimensional audio space, where all theaudiofiles 402, 404, 406 are being played simultaneously, and as usermoves about the three-dimensional audio space (i.e., gets closer tocertain audiofiles and further from others) the volumes of therespective audiofiles changes based on the virtual distance between theuser and the audiofiles within the three-dimensional audio space. Inanother configuration, the user is again browsing in a three-dimensionalaudio space with all of the respective audiofiles 402, 404, 406 againplaying simultaneously. However, in this embodiment, the audiofiles allplay in their entirety, with the representative segments increasing involume for each respective audiofile as those respective segments areplayed.

Having disclosed some basic system components and concepts, thedisclosure now turns to the exemplary method embodiment shown in FIG. 5.For the sake of clarity, the method is described in terms of anexemplary system 100 as shown in FIG. 1 configured to practice themethod. The steps outlined herein are exemplary and can be implementedin any combination thereof, including combinations that exclude, add, ormodify certain steps.

The system 100 analyzes a first audiofile, to yield a first analysis,wherein the first analysis identifies a first segment of a firstplurality of segments within the first audiofile, the first segmentbeing one of a most interesting segment, a most important segment, amost relevant segment, and a most representative segment (502). Thesystem 100 also analyzes a second audiofile, to yield a second analysis,wherein the second analysis identifies a second segment of a secondplurality of segments within the second audiofile, the second segmentcomprising one of a most interesting segment, a most important segment,a most relevant segment, and a most representative segment (504). Thesystem 100 can then present the first segment as a representativesegment of the first audiofile and the second segment as arepresentative of the second audiofile within a three-dimensional audiospace (506).

The presenting of the first segment and the second segment can occurwithin the three-dimensional audio space simultaneously, where thepresenting is performed by moving a respective segment closer to a userwithin the three-dimensional audio space during play of the respectivesegment, and away from the user while not playing the respectivesegment. The user can then select an audiofile based on their behaviorwithin the three-dimensional audio space. For example, within thevirtual environment of the three-dimensional audio space, the user mightnot move for a certain period of time. Another example would be the userproviding input from the real-world into the three-dimensional audiospace, or the user listening to the entirety of the audiofile (asopposed to only the representative segment).

User preferences which can affect which segment is selected as therepresentative segment can include user history (such as selection andbrowsing history), age, job title, place of employment, recentconversations, calendar information (such as what meetings areupcoming), family information (names of family, professions of familymembers, job titles of family members, etc.). User identity can affectthe which segments are selected by identifying, based on the useridentity, a ranked list of topics important to the user which can beused in turn to determine which segments best represent the audiofiles.The system 100 can also rely on context information in determining whichsegment should be selected as the representative segment. Examples ofcontext information include time, location, a user identity of a user,an age of each audiofile, a content of a request, an age of the user,and a category of the each audiofile.

The system 100 can also select the representative segments based on thepopularity of the segment. For example, if one segment in the audiofilehas been played over a million times, and another segment has only beenplayed a hundred times, the segment which has been played a milliontimes will be determined to be more popular. More specifically, thepopular segment can be determined based on a ratio of times a respectivesegment has been played versus times other segments in the audiofilehave been played. Such determinations of popularity can have a timefactor. For example, if a particular segment has been very popular inthe past day, but has not been the most popular over the lifetime of theaudiofile, the system 100 can determine that the particular segmentshould be selected as the most popular segment. Other time periods(hours, days, weeks, months, etc.) are likewise within the scope of thisdisclosure for determining popularity of a respective segment.

Embodiments within the scope of the present disclosure may also includetangible and/or non-transitory computer-readable storage media forcarrying or having computer-executable instructions or data structuresstored thereon. Such tangible computer-readable storage media can be anyavailable media that can be accessed by a general purpose or specialpurpose computer, including the functional design of any special purposeprocessor as described above. By way of example, and not limitation,such tangible computer-readable media can include RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to carryor store desired program code means in the form of computer-executableinstructions, data structures, or processor chip design. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or combinationthereof) to a computer, the computer properly views the connection as acomputer-readable medium. Thus, any such connection is properly termed acomputer-readable medium. Combinations of the above should also beincluded within the scope of the computer-readable media.

Computer-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Computer-executable instructions also includeprogram modules that are executed by computers in stand-alone or networkenvironments. Generally, program modules include routines, programs,components, data structures, objects, and the functions inherent in thedesign of special-purpose processors, etc. that perform particular tasksor implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of the program code means for executing steps of the methodsdisclosed herein. The particular sequence of such executableinstructions or associated data structures represents examples ofcorresponding acts for implementing the functions described in suchsteps.

Other embodiments of the disclosure may be practiced in networkcomputing environments with many types of computer systemconfigurations, including personal computers, hand-held devices,multi-processor systems, microprocessor-based or programmable consumerelectronics, network PCs, minicomputers, mainframe computers, and thelike. Embodiments may also be practiced in distributed computingenvironments where tasks are performed by local and remote processingdevices that are linked (either by hardwired links, wireless links, orby a combination thereof) through a communications network. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices.

The various embodiments described above are provided by way ofillustration only and should not be construed to limit the scope of thedisclosure. For example, the principles herein apply both to presentingrepresentative segments of audiofiles both in and out ofthree-dimensional audio spaces. Various modifications and changes may bemade to the principles described herein without following the exampleembodiments and applications illustrated and described herein, andwithout departing from the spirit and scope of the disclosure.

We claim:
 1. A method comprising: analyzing a first audiofile, to yielda first analysis, wherein the first analysis identifies a first segmentof a first plurality of segments within the first audiofile, the firstsegment being one of a most interesting segment, a most importantsegment, a most relevant segment, and a most representative segment;analyzing a second audiofile, to yield a second analysis, wherein thesecond analysis identifies a second segment of a second plurality ofsegments within the second audiofile, the second segment comprising oneof a most interesting segment, a most important segment, a most relevantsegment, and a most representative segment; and presenting the firstsegment as a representative segment of the first audiofile and thesecond segment as a representative of the second audiofile within athree-dimensional audio space.
 2. The method of claim 1, furthercomprising: presenting the first segment and the second segment withinthe three-dimensional audio space simultaneously, wherein the presentingcomprises moving a respective segment closer to a user within thethree-dimensional audio space during play of the respective segment, andaway from the user while not playing the respective segment.
 3. Themethod of claim 2, further comprising receiving a selection of anaudiofile based on a behavior of the user within the three-dimensionalaudio space.
 4. The method of claim 1, wherein the first segment and thesecond segment are based on user preferences.
 5. The method of claim 4,wherein the first segment and the second segment are further based oncontext information.
 6. The method of claim 5, wherein the contextinformation comprises one of: time, location, a user identity of a user,an age of each audiofile, a content of a request, an age of the user,and a category of the each audiofile.
 7. The method of claim 1, thefirst segment and the second segment represent a most popular segment ina respective audiofile.
 8. The method of claim 7, wherein the mostpopular segment is based on a ratio of times a respective segment hasbeen played versus times other segments in each respective audiofilehave been played.
 9. The method of claim 1, further comprising:identifying, based on an identity of a user, a ranked list of topicsimportant to the user, wherein the most important segment of the firstaudiofile and the most important segment of the second audiofile isbased on the ranked list of topics.
 10. A system comprising: aprocessor; and a computer-readable storage medium having instructionsstored which, when executed by the processor, cause the processor toperform operations comprising: analyzing a first audiofile, to yield afirst analysis, wherein the first analysis identifies a first segment ofa first plurality of segments within the first audiofile, the firstsegment being one of a most interesting segment, a most importantsegment, a most relevant segment, and a most representative segment;analyzing a second audiofile, to yield a second analysis, wherein thesecond analysis identifies a second segment of a second plurality ofsegments within the second audiofile, the second segment comprising oneof a most interesting segment, a most important segment, a most relevantsegment, and a most representative segment; and presenting the firstsegment as a representative segment of the first audiofile and thesecond segment as a representative of the second audiofile within athree-dimensional audio space.
 11. The system of claim 10, thecomputer-readable storage medium having additional instructions storedwhich, when executed by the processor, cause the processor to performoperations comprising: presenting the first segment and the secondsegment within the three-dimensional audio space simultaneously, whereinthe presenting comprises moving a respective segment closer to a userwithin the three-dimensional audio space during play of the respectivesegment, and away from the user while not playing the respectivesegment.
 12. The system of claim 11, the computer-readable storagemedium having additional instructions stored which, when executed by theprocessor, cause the processor to perform operations comprisingreceiving a selection of an audiofile based on a behavior of the userwithin the three-dimensional audio space.
 13. The system of claim 10,wherein the first segment and the second segment are based on userpreferences.
 14. The system of claim 13, wherein the first segment andthe second segment are further based on context information.
 15. Thesystem of claim 14, wherein the context information comprises one of:time, location, a user identity of a user, an age of each audiofile, acontent of a request, an age of the user, and a category of the eachaudiofile.
 16. The system of claim 10, the first segment and the secondsegment represent a most popular segment in a respective audiofile. 17.The system of claim 16, wherein the most popular segment is based on aratio of times a respective segment has been played versus times othersegments in each respective audiofile have been played.
 18. The systemof claim 10, the computer-readable storage medium having additionalinstructions stored which, when executed by the processor, cause theprocessor to perform operations comprising: identifying, based on anidentity of a user, a ranked list of topics important to the user,wherein the most important segment of the first audiofile and the mostimportant segment of the second audiofile is based on the ranked list oftopics.
 19. A computer-readable storage device having instructionsstored which, when executed by a computing device, cause the computingdevice to perform operations comprising: analyzing a first audiofile, toyield a first analysis, wherein the first analysis identifies a firstsegment of a first plurality of segments within the first audiofile, thefirst segment being one of a most interesting segment, a most importantsegment, a most relevant segment, and a most representative segment;analyzing a second audiofile, to yield a second analysis, wherein thesecond analysis identifies a second segment of a second plurality ofsegments within the second audiofile, the second segment comprising oneof a most interesting segment, a most important segment, a most relevantsegment, and a most representative segment; and presenting the firstsegment as a representative segment of the first audiofile and thesecond segment as a representative of the second audiofile within athree-dimensional audio space.
 20. The computer-readable storage deviceof claim 19, having additional instructions stored which, when executedby the computing device, cause the computing device to performoperations comprising: presenting the first segment and the secondsegment within the three-dimensional audio space simultaneously, whereinthe presenting comprises moving a respective segment closer to a userwithin the three-dimensional audio space during play of the respectivesegment, and away from the user while not playing the respectivesegment.